Integrated Business Data System for Predictive Decision-Making

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Solution Overview

Problem

Current business software solutions fail to integrate fully the retrieval, analysis, and transformation of high-volume business data from diverse sources, leading to inefficiencies and potential errors in decision-making processes.

Innovation Solution

A distributed system that integrates business data retrieval, analysis, and decision-making, utilizing a business data retrieval engine, a business data analysis engine, and a business decision and action path simulation engine to process data from multiple sources and provide predictive analytics and risk assessments.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If multiple separate software packages are used for data retrieval, analysis, and decision-making, then each software can specialize in its specific function, but manual data transformation between packages is required which introduces errors and reduces efficiency

Engineering Contradiction:

Improvefunctional specializationVSAvoiddecision-making accuracy

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent combines multiple separate software packages (data retrieval, analysis, and decision-making tools) into a single integrated business operating system. This integration eliminates the need for manual data transformation between packages, thereby reducing errors while maintaining functional specialization through modular architecture.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The business operating system is designed as a universal platform that performs multiple functions including data retrieval, analysis, and decision-making support within a single system. This multi-functional approach allows the system to handle diverse business operations without requiring external software packages.

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Adaptability or versatility

If manual data transformation is performed between software packages, then data can be adapted to different formats, but human resources are wasted and errors are introduced at critical process points

Engineering Contradiction:

Improvedata format compatibilityVSAvoiddata processing efficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent replaces manual mechanical data transformation processes with automated electronic data processing within the integrated system. The system automatically transforms and adapts data between different formats using computerized algorithms, eliminating human intervention and associated errors while improving processing efficiency.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If a fully integrated system is created for data retrieval, analysis, and predictive decision-making, then efficiency and reliability are improved, but system complexity increases

Engineering Contradiction:

Improvedecision-making efficiencyVSAvoidsystem integration complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The business operating system is segmented into distinct functional modules including data retrieval components, analysis engines, and decision-making tools. This modular segmentation allows the system to maintain high integration and efficiency while managing complexity through organized, independent components that can be developed and maintained separately.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20250193255A1System for automated capture and analysis of business information for reliable business venture outcome prediction

Publication Date: 2025.06.12 QPX LLC

AI summary

A system for fully integrated collection of business impacting data, analysis of that data and generation of both analysis-driven business decisions and analysis driven simulations of alternate candidate business actions has been devised and reduced to practice. This business operating system may be used predict the outcome of enacting candidate business decisions based upon past and current business data retrieved from both within the corporation and from a plurality of external sources pre-programmed into the system. Both single parameter set and multiple parameter set analyses are supported. Risk to value estimates of candidate decisions are also calculated.